Gender: Male 
Age: 35-44
Nationality: United States
Ethnicity: White / Caucasian 
Marital status: Single 
First language: English 
Religion: Nothing 
Education: Undergraduate degree
Mother's education: Undergraduate degree
Father's education: High school or below
Self-assessed socioeconomic status (1-10): 2
Home: Other (Please specify) live with parents
Employment: Not employed and not looking for work
Mother's occupation: Clerical support workers (those who perform clerical duties such as organizing, storing, computing and retrieving information)
Father's occupation: Service and sales workers (whose who provide personal and protective services related to travel, housekeeping, catering, personal care, protection against fire and unlawful acts)
Hobbies: Listen to hiphop and rap;Use social media;Exercise;Watch sports 
Devices used daily: Laptop;Smartphone;Tablet 
NLP tools known: Sentiment analysis (e.g. automatically detect if user reviews are positive or negative);Grammar checker (i.e., correcting grammar mistakes);Spell checker (i.e., correcting misspellings);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Machine translation (e.g. translate Chinese or Russian into English, and vice versa);Paraphrasing and Summarisation (i.e., automatically produce alternative descriptions of written text);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants);Dialog technology (e.g. chatbots that communicate with you such as chatGPT);Speech-to-Text (i.e. a computer transcribing your spoken language to written language);Text-to-Speech (i.e, computers being able to read out loud written language);Reading text from scanned documents (i.e. “Optical character recognition” or OCR. Given an image representing printed text, determine the corresponding text.) 
NLP tools used: Spell checker (i.e., correcting misspellings);Grammar checker (i.e., correcting grammar mistakes);E-mail spam detection (i.e., automatically send spam e-mails to your Trash folder);Machine translation (e.g. translate Chinese or Russian into English, and vice versa);Paraphrasing and Summarisation (i.e., automatically produce alternative descriptions of written text);Question Answering & Search Engine. (e.g., browsers or ask questions to smart devices/assistants);Dialog technology (e.g. chatbots that communicate with you such as chatGPT);Speech-to-Text (i.e. a computer transcribing your spoken language to written language);Text-to-Speech (i.e, computers being able to read out loud written language);Reading text from scanned documents (i.e. “Optical character recognition” or OCR. Given an image representing printed text, determine the corresponding text.) 
Frequency of LLM use: Every day
LLMs used: ChatGPT;Google Gemini;Grok 
LLM use cases: Translation;Brainstorming;Writing (e.g., composing emails);Paraphrasing or finding synonyms;Proofreading/Editing (e.g., grammar, spelling, structure improvements);Digital content creation (e.g., creation of social media content);Generic chatbot conversation;Solving math or logical problems;Analyze data;Generate art;Learning (e.g., explaining complex concepts in simple terms);Answering questions about general knowledge;Summarizing long texts;Coding 
Contexts of LLM use: Entertainment;Learning;Personal;Technical;Creative or artistic;Work 
Prompt 1: I noticed that Emma Raducanu hits the ball right back to her opponents racquet while they seem to hit cross court and make her chase the ball back and forth on the baseline. No bullets, is this a flaw in her game or an advantage and why?
Prompt 2: read this and tell me if what i said in the past prompt is helping or hurting her:  Australian Open: Iga Swiatek is in total control during a 6-1, 6-0 rout of Emma Raducanu HOWARD FENDRICH Sat, January 18, 2025 at 3:41 AM MST and I (article included)
Prompt 3: so she should not hit the ball right back to players like Iga's racquet correct or no and why also no bullets please
Prompt 4: Listen, Emma Raducanu has said it's above me to run an agency and that I don't know what I'm talking about because I tried to give her advice about how to manage her career and her game. This deeply offended me and I tried using ChatGPT to create my own tennis agency but it was too big of an undertaking given the previous models limitations. Now that we have o1 I want to try to make it happen. First off give me some strategies we can use to launch a tennis agency from the ground up on a shoestring budget and compete with the likes of IMG and Octagon.
Prompt 5: what would these people be searching for and where would they look, what would they expect to find when they come acrossed it? I want to know the inside baseball on how we can get our foot in the door asap and start earning real actual money as a tennis agency no dream stuff.
Prompt 6: give me a killer keyword list with some possible related domains to cover the niche, keep it tight with nothing but an excellent strategy
Prompt 7: what's the killer combo for a domain name give me 5 of them
Prompt 8: hmm it needs to be something they might search for when looking for an agency so we can rank the EMD
Prompt 9: shorter tighter, the competition isn't too stiff, what's the killer domain that helps us dominate the niche, us all your resources to come up with the best one.
Prompt 10: I can get pro tennis agency, would I get keyword searches for it? show me semantically related keywords and the keyword itself with monthly search volume and cpc stats
Comments: I use them nonstop, I've created a ton of coding projects, I've figured out really complex things that always perplexed / vexed me.